Intravascular optical coherence tomography (iOCT) is an emerging image technology that will play a central role in advancing our understanding of human vascular biology and will contribute to informed treatment decisions. OCT's high speed acquisition, good tissue contrast, low noise, and excellent resolution reportedly enables one to image plaque components such as the thick/thin fibrous cap, lipid core, calcifications, and possibly lipid filled macrophages. However, at 100 images/sec, the amount of image data and details generated by OCT can be overwhelming to the practicing clinician. Our long-range goal is to develop image visualization and computer aided diagnosis (CAD) methods that we hypothesize will enable one using iOCT to detect rapidly and reliably findings of interest, and to make informed treatment decisions. In this preliminary study, we propose to obtain vessel segments from cadavers and create an iOCT database containing lesions confirmed with heretofore-unavailable accuracy, to potentially validate emergent iOCT findings (e.g., neovasculature), to perform a pilot study of the accuracy of readings by cardiologists, and to identify potential methods for CAD processing. Key will be the Case cryo-imaging/histology system developed by us, a section-and-image system that provides microscopic 3D data sets of an entire vessel segment as well as selected histology. With it, careful experimental methods, and 3D image registration, we will create a unique iOCT image database with accurately registered, independently confirmed findings. If successful, this proposed research will set the stage for a comprehensive program to optimize iOCT acquisition, CAD processing, and visualization to enable plaque characterization and to assess vulnerability. PUBLIC HEALTH RELEVANCE: Our interdisciplinary team will develop methods for improved detection and staging of blood vessel disease. Intravascular optical coherence tomography (iOCT) will be used to obtain very high resolution, microscopic images of the vessel wall. We will assess the ability of this technology and associated software to determine the type of plaque in the lesion and its vulnerability to rupture, a potentially life threatening event.